Results from the laboratory demonstration of the non-linear curvature wavefront sensor

Mala Mateen, Vincent Garrel, Michael Hart, Olivier Guyon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In this paper we show why a non-linear curvature wavefront sensor (nlCWFS) is superior to both Shack-Hartmann wavefront sensor (SHWFS) and conventional curvature wavefront sensor (cCWFS) for sensing mv < 15 natural guide stars. We have developed, an experimental setup aimed at comparing the the rms wavefront error obtained, with the nlCWFS and the SHWFS. We describe our experimental setup and present results from the laboratory demonstration of the nlCWFS. The non-linear approach, builds on the successful curvature wavefront sensing concept. The wavefront is reconstructed from the defocused pupil images using the Gerchberg-Saxton (GS) phase diversity algorithm. We compare results obtained from reconstructing the wavefront using a Shack-Hartmann wavefront sensor (SHWFS) and a nlCWFS for a monochromatic source. We discuss approaches to overcome non-linearity issues and discuss the challenge of using two WFSs in the same spatiotemporal control regime and the implementation of the nlCWFS on the 6.5 m MMT.

Original languageEnglish (US)
Title of host publicationAdaptive Optics Systems II
EditionPART 1
DOIs
StatePublished - 2010
EventAdaptive Optics Systems II - San Diego, CA, United States
Duration: Jun 27 2010Jul 2 2010

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
NumberPART 1
Volume7736
ISSN (Print)0277-786X

Other

OtherAdaptive Optics Systems II
Country/TerritoryUnited States
CitySan Diego, CA
Period6/27/107/2/10

Keywords

  • Adaptive optics
  • Curvature wavefront sensor
  • Extreme-adaptive optics
  • Gerchberg-Saxton
  • Non-linear curvature wavefront sensor
  • Phase diversity
  • Shack-Hartmann wavefront sensor
  • Wavefront sensitivity

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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